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A sequential, multiple assignment, randomized trial design with a tailoring function.
- Source :
-
Statistics in Medicine . 9/20/2024, Vol. 43 Issue 21, p4055-4072. 18p. - Publication Year :
- 2024
-
Abstract
- We present a trial design for sequential multiple assignment randomized trials (SMARTs) that use a tailoring function instead of a binary tailoring variable allowing for simultaneous development of the tailoring variable and estimation of dynamic treatment regimens (DTRs). We apply methods for developing DTRs from observational data: tree‐based regression learning and Q‐learning. We compare this to a balanced randomized SMART with equal re‐randomization probabilities and a typical SMART design where re‐randomization depends on a binary tailoring variable and DTRs are analyzed with weighted and replicated regression. This project addresses a gap in clinical trial methodology by presenting SMARTs where second stage treatment is based on a continuous outcome removing the need for a binary tailoring variable. We demonstrate that data from a SMART using a tailoring function can be used to efficiently estimate DTRs and is more flexible under varying scenarios than a SMART using a tailoring variable. [ABSTRACT FROM AUTHOR]
- Subjects :
- *REINFORCEMENT learning
*CLINICAL trials
*TAILORING
*PROBABILITY theory
Subjects
Details
- Language :
- English
- ISSN :
- 02776715
- Volume :
- 43
- Issue :
- 21
- Database :
- Academic Search Index
- Journal :
- Statistics in Medicine
- Publication Type :
- Academic Journal
- Accession number :
- 179140478
- Full Text :
- https://doi.org/10.1002/sim.10161